Managing Product Returns for Reverse Logistics
Managing product returns for reverse logistics
This paper provides a framework to manage product returns for reverse logistics. It takes a specific product catalog in India as an example.
It utilizes an integrated framework to estimate returns of products. Next step, it makes decisions on operations, such as disposition, location and capacity of facilities. After that, take strategic, operational and customer service-related constraints into to consideration to give a time horizon for returned products.
It provides the basic flow of reverse logistics activities and explains them in detail by the concept model. Then, it integrated these physical flows with the data and estimation. In terms of the data collection, it can be divided into two main groups. First is the Return data, which is related to the product, includes the types and the time-varying. Second is Operations and cost related parameters. It provides the cost of each activity which is related to the revers logistics. From the perspective of forecasting techniques, they neither consider returns only dependent on demand nor do they according to the historical data for estimating. Instead, they utilize a causal System dynamics model which associates returns with number of products-in-use, estimated demand and PLC. In addition, environmental protection policies and green index and utility factor also are taking into consideration.
Admittedly, there are many parameter I can’t understand them perfect. However, I can recognize the relationship between those causes and return product, in terms of volume, value and methods of disposing.
But there is still some limitation of this integrated model. From my point of view, there are some estimations are over simplify. It utilize the mathematical method to transfer the causal relationship into quantity, which may make deviations and led a big different. What is more, the integrated model is not suit for the rapid develop of upgrade of products. It
This paper provides a framework to manage product returns for reverse logistics. It takes a specific product catalog in India as an example.
It utilizes an integrated framework to estimate returns of products. Next step, it makes decisions on operations, such as disposition, location and capacity of facilities. After that, take strategic, operational and customer service-related constraints into to consideration to give a time horizon for returned products.
It provides the basic flow of reverse logistics activities and explains them in detail by the concept model. Then, it integrated these physical flows with the data and estimation. In terms of the data collection, it can be divided into two main groups. First is the Return data, which is related to the product, includes the types and the time-varying. Second is Operations and cost related parameters. It provides the cost of each activity which is related to the revers logistics. From the perspective of forecasting techniques, they neither consider returns only dependent on demand nor do they according to the historical data for estimating. Instead, they utilize a causal System dynamics model which associates returns with number of products-in-use, estimated demand and PLC. In addition, environmental protection policies and green index and utility factor also are taking into consideration.
Admittedly, there are many parameter I can’t understand them perfect. However, I can recognize the relationship between those causes and return product, in terms of volume, value and methods of disposing.
But there is still some limitation of this integrated model. From my point of view, there are some estimations are over simplify. It utilize the mathematical method to transfer the causal relationship into quantity, which may make deviations and led a big different. What is more, the integrated model is not suit for the rapid develop of upgrade of products. It